Technology
Artificial intelligence is becoming increasingly vital in this modern era. It is transforming and restructuring how we interact with technology, enabling machines to do human tasks and make decisions. But there is a need to implement social intelligence with artificial intelligence, according to researchers.
Social intelligence in AI is a type of AI capable of understanding and interpreting human behaviour, habits and emotions. If we glance at an example of Siri, Alexa or Google Assistant, which may be able to organise and queue up meetings and reminders for us, they cannot arrange and prioritize the meetings on their own. AI is a powerful tool for improving our lives but at the same time have a dearth of social skills.
Artificial Social Intelligence (ASI)
ASI would soon become a big challenge to AI. It requires a deep understanding of the complexities of human behaviour and emotion. AI should be ready to respond to subtle cues, recognize the mood and motives of an individual, and hence effectively communicate and function in a socially appropriate manner. It is a tough task, as AI has no inherent understanding of these concepts. It must be taught through programming, which may result in a laborious process. Artificial social intelligence (ASI) includes the theory of mind, social perception and social interaction. The content of ASI is very large. When AI transforms into ASI, it would help us to collaborate and connect more efficiently with people as well as machines.
The potential of ASI
This technology can be used to improve customer service, facilitate finer communication between humans & machines, and even revolutionise the way we think about and interact with the world in ways we may not have been able to. ASI could make our lives more stressful free and hence we can dedicate time to our personal development. Ultimately, ASI can help us better understand ourselves and our environment, and make our lives easier and more efficient.
ASI requires an open-ended environment
Experts say that a comprehensive approach is required to imitate how human beings interact and associate with each other and the world around them. For this to happen, open-ended and bilateral circumstances are required. The ultimate task is to create datasets, define new problems & environments, work on protocols and eventually construct new computational models. ASI needs more advanced AI-driven applications, such as natural language processing (NLP), facial recognition, and computer vision.
The Conclusion
Social awareness can be beneficial to AI in many ways. AI can also leverage social awareness to accurately interpret images, videos, and texts to better understand the environment and people’s behaviour. Finally, social awareness can help AI systems make decisions that are more in line with human values and ethics. Artificial social intelligence can offer more efficient ways of working. Finally, ASI can be used to monitor and provide feedback on progress and performance, enabling humans to make more informed decisions and be more in control of their lives.
